code: def _maybe_mask_fixed_inputs(
      fixed_inputs, feature_ndims, fixed_inputs_is_missing=None
  ):
      """Mask fixed inputs to zero when missing."""
      if fixed_inputs_is_missing is None:
          return fixed_inputs
      pad_shapes = lambda nd: util.pad_shape_with_ones(  # pylint:disable=g-long-lambda
          fixed_inputs_is_missing, nd, start=-1
      )
      fixed_inputs_is_missing = tf.nest.map_structure(
          pad_shapes, feature_ndims
      )
      # TODO(b/276969724): Mask out missing index points to something in the
      # support of the kernel.
      mask = lambda m, x: tf.where(
          m, dtype_util.as_numpy_dtype(x.dtype)(0), x
      )
      fixed_inputs = tf.nest.map_structure(
          mask, fixed_inputs_is_missing, fixed_inputs
      )
      return fixed_inputs
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math.psd_kernels import positive_semidefinite_kernel
  from tensorflow_probability.python.math.psd_kernels.internal import util
label_desc: Use image node_id 3 for calling a global function with example usage: _maybe_mask_fixed_inputs(fixed_inputs, feature_ndims, fixed_inputs_is_missing) and returns: fixed_inputs, fixed_inputs